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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A multi-source information transfer learning method with subdomain adaptation for cross-domain fault diagnosis
Jinghui Tian, Dongying Han, Mengdi Li, et al.
Knowledge-Based Systems (2022) Vol. 243, pp. 108466-108466
Closed Access | Times Cited: 113

Showing 26-50 of 113 citing articles:

Semi-supervised prototype network based on compact-uniform-sparse representation for rotating machinery few-shot class incremental fault diagnosis
Yu Zhang, Dongying Han, Peiming Shi
Expert Systems with Applications (2024) Vol. 255, pp. 124660-124660
Closed Access | Times Cited: 7
Selecting subsets of source data for transfer learning with applications in metal additive manufacturing
Yifan Tang, Mostafa Rahmani Dehaghani, Pouyan Sajadi, et al.
Journal of Intelligent Manufacturing (2024)
Closed Access | Times Cited: 6
A Multi-Source Domain Feature-Decision Dual Fusion Adversarial Transfer Network for Cross-Domain Anti-Noise Mechanical Fault Diagnosis in Sustainable City
Changdong Wang, Huamin Jie, Jingli Yang, et al.
Information Fusion (2024) Vol. 115, pp. 102739-102739
Closed Access | Times Cited: 6
Gradient-based domain-augmented meta-learning single-domain generalization for fault diagnosis under variable operating conditions
Chuanxia Jian, Heen Chen, Chaobin Zhong, et al.
Structural Health Monitoring (2024) Vol. 23, Iss. 6, pp. 3904-3920
Closed Access | Times Cited: 5
Cross-Domain Compound Fault Diagnosis of Machine-Level Motors via Time–Frequency Self-Contrastive Learning
Yiming He, Chao Zhao, Weiming Shen
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 7, pp. 9692-9701
Closed Access | Times Cited: 5
A novel sliding mixing graph contrastive domain adaptation method for fault diagnosis under time-varying speeds
Kai Chen, Zong Meng, Dengyun Sun, et al.
Expert Systems with Applications (2025), pp. 126576-126576
Closed Access
An unsupervised multi-level fusion domain adaptation method for transfer diagnosis under time-varying working conditions
Cuiying Lin, Yun Kong, Qinkai Han, et al.
Mechanical Systems and Signal Processing (2025) Vol. 228, pp. 112458-112458
Closed Access
Rolling mill health states diagnosing method based on multi-sensor information fusion and improved DBNs under limited datasets
Yue Yu, Peiming Shi, Jinghui Tian, et al.
ISA Transactions (2022) Vol. 134, pp. 529-547
Closed Access | Times Cited: 26
Deep transfer learning with metric structure for fault diagnosis
Yaqi Xiao, Jiongqi Wang, Zhangming He, et al.
Knowledge-Based Systems (2022) Vol. 256, pp. 109826-109826
Closed Access | Times Cited: 23
Intelligent fault diagnosis via ring-based decentralized federated transfer learning
Lanjun Wan, Jiaen Ning, Yuanyuan Li, et al.
Knowledge-Based Systems (2023) Vol. 284, pp. 111288-111288
Closed Access | Times Cited: 15
A meta-learning network with anti-interference for few-shot fault diagnosis
Zhiqian Zhao, Runchao Zhao, Xianglin Wu, et al.
Neurocomputing (2023) Vol. 552, pp. 126551-126551
Closed Access | Times Cited: 14
Improved metric-based meta learning with attention mechanism for few-shot cross-domain train bearing fault diagnosis
Hao Zhong, Deqiang He, Zhenpeng Lao, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 7, pp. 075101-075101
Closed Access | Times Cited: 4
Deep conditional adversarial subdomain adaptation network for unsupervised mechanical fault diagnosis
Guiping Chen, Dong Xiang, Tingting Liu, et al.
Knowledge-Based Systems (2024) Vol. 300, pp. 112180-112180
Closed Access | Times Cited: 4
Intelligent fault diagnosis of rolling bearing based on an active federated local subdomain adaptation method
Xiaoming Yuan, Dongling Shi, Nian Shi, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102807-102807
Closed Access | Times Cited: 4
A novel dual attention network for sparse reconstruction of turbine blade surface fields
Zuobiao Li, Liangjun Su, Zhongqi Liu, et al.
Energy (2025), pp. 134644-134644
Closed Access
SIGTN: A Novel Structural Infomax Graph Transfer Networks for Rotating Machinery Fault Diagnosis in Cross-Condition and Cross-Equipment Scenarios
Kongliang Zhang, Hongkun Li, Shunxin Cao, et al.
Reliability Engineering & System Safety (2025), pp. 110898-110898
Closed Access
A novel multiple-prototype and domain adversarial network for few-shot cross-domain fault diagnosis
Peiming Shi, Siyang Dai, Xuefang Xu, et al.
Measurement Science and Technology (2025) Vol. 36, Iss. 3, pp. 036134-036134
Closed Access
A Multi-Gradient Hierarchical Domain Adaptation Network for transfer diagnosis of bearing faults
Jun Chen, Hui Liu
Expert Systems with Applications (2023) Vol. 225, pp. 120139-120139
Closed Access | Times Cited: 11
A progressive multi-source domain adaptation method for bearing fault diagnosis
Xiaorong Zheng, Zhiwei He, Jiahao Nie, et al.
Applied Acoustics (2023) Vol. 216, pp. 109797-109797
Closed Access | Times Cited: 11
Novel Adversarial Unsupervised Subdomain Adaption Multi-Channel Deep Convolutional Network for Cross-Operating Fault Diagnosis of Rolling Bearings
B. Zhang, Tianlong Huo, Zheng Liu, et al.
IEEE Access (2024) Vol. 12, pp. 42068-42082
Open Access | Times Cited: 3
Time-Varying Online Transfer Learning for Intelligent Bearing Fault Diagnosis With Incomplete Unlabeled Target Data
Yuxuan Zhou, Yining Dong, Gang Tang
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 6, pp. 7733-7741
Closed Access | Times Cited: 18
An attention enhanced dilated CNN approach for cross-axis industrial robotics fault diagnosis
Yuxin Liu, Chong Chen, Tao Wang, et al.
Autonomous Intelligent Systems (2022) Vol. 2, Iss. 1
Open Access | Times Cited: 16
A fault location method based on ensemble complex spatio-temporal attention network for complex systems under fluctuating operating conditions
Jingli Yang, Tianyu Gao, Ge Yan, et al.
Applied Soft Computing (2023) Vol. 144, pp. 110489-110489
Closed Access | Times Cited: 10
A fine-grained feature decoupling based multi-source domain adaptation network for rotating machinery fault diagnosis
Xiaorong Zheng, Jiahao Nie, Zhiwei He, et al.
Reliability Engineering & System Safety (2023) Vol. 243, pp. 109892-109892
Closed Access | Times Cited: 10
Fault diagnosis of bearings using a two-stage transfer alignment approach with semantic consistency and entropy loss
Jichao Zhuang, Yudong Cao, Minping Jia, et al.
Expert Systems with Applications (2023) Vol. 226, pp. 120274-120274
Closed Access | Times Cited: 9

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